Digital signal processing (DSP) Books

Book SynopsisThe book explains the important concepts and principles of image processing to implement the algorithms and techniques to discover new problems and applications. It contains numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. It presents essential background theory, shape methods, texture about new methods, and techniques for image processing and pattern recognition. It maintains a good balance between a mathematical background and practical implementation. This book also contains the comparison table and images that are used to show the results of enhanced techniques. This book consists of novel concepts and hybrid methods for providing effective solutions for society. It also includes a detailed explanation of algorithms in various programming languages like MATLAB, Python, etc. The security features of image processing like image watermarking and image encryption etc. are also discussed in this book. This book will be useful for those who are working in the field of image processing, pattern recognition, and security for digital images. This book targets researchers, academicians, industry, and professionals from R&D organizations, and students, healthcare professionals working in the field of medical imaging, telemedicine, cybersecurity, data scientist, artificial intelligence, image processing, digital hospital, intelligent medicine.Table of ContentsChapter 1: Introduction of Image processingChapter 2: Image Enhancement Chapter 3: Image segmentation and image colorization Chapter 4: Image classification, fusion, and reconstruction Chapter 5: Feature Extraction Chapter 6: Pattern recognition and computer vision applications in Agriculture, GIS, Surveillance and Robotics. Chapter 7: Statistical Pattern Recognition and Supervised Learning Chapter 8: Artificial Intelligence, Machine and Deep Learning for pattern recognition Chapter 9: Image compression and Cloud Imaging Chapter 10: Neural network and data science in image processing Chapter 11: Imaging acquisition and Biometrics Chapter 12: Application of medical Imaging in telemedicine. Chapter 13: Digital Image security, privacy, and future challenges Chapter 14: AI methodologies for medical images analysis

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Book SynopsisThe book is a collection of best selected research papers presented at the International Conference on Advances in Information Communication Technology and Computing (AICTC 2021), held in Government Engineering College Bikaner, Bikaner, India, during 20–21 December 2021. The book covers ICT-based approaches in the areas of ICT for energy efficiency, life cycle assessment of ICT, green IT, green information systems, environmental informatics, energy informatics, sustainable HCI or Artificial intelli computational sustainability.Table of ContentsChapter 1. Smart Society Development Analysis and Controlbased on an Inductive Inference Method.- Chapter 2. The Emergence of sustainability Adoption in the Healthcare Sector during Covid-19.- Chapter 3. Ultra Wide Band Radar System for Respiratory Detection and Localization of Static Multi-Targets in LOS confined Environment.- Chapter 4. Omnichannel Integration Quality, Perceived Value and Brand Loyalty in the consumer electronics market: The Mediating effect of Consumer Personality.- Chapter 5. Examining the Impact of Incorporating Big Data Analytics in Agriculture.- Chapter 6. Online Teaching Strategies for IT Education.- Chapter 7. Smart and Intelligent Health Monitoring System.- Chapter 8. Energy Efficient OLSR Routing Protocol for Flying Ad-Hoc Networks.- Chapter 9. Challenges in Malware Detection and effecting areas: Survey.- Chapter 10. Integrated Smart IoT Infrastructure Management using Window Blockc­­hain and Whale LSTM Approaches.- Chapter 11. Driving analysis for load and fuel consumption using OBD II diagnostics.- Chapter 12. 2D and 3D Human Pose Estimation and Analysis using Deep Learning.- Chapter 13. The Comprehensive Art of Atmospheric Turbulence Mitigation Methodologies for Visible and Infrared Sequences.- Chapter 14. Graphical interpretation and multi-dimensional data visualization on Heart Disease Dataset.

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Book SynopsisThis book focuses on soft computing and how it can be applied to solve real-world problems arising in various domains, ranging from medicine and healthcare, to supply chain management, image processing, and cryptanalysis. It gathers high-quality papers presented at the International Conference on Soft Computing: Theories and Applications (SoCTA 2021), organized online. The book offers valuable insights into soft computing for teachers and researchers alike; the book will inspire further research in this dynamic field.

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Book SynopsisThis book gathers selected papers presented at the conference “Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology,” one of the first initiatives devoted to the problems of 3D imaging in all contemporary scientific and application areas. The two volumes of the book cover wide area of the aspects of the contemporary multidimensional imaging and outline the related future trends from data acquisition to real-world applications based on new techniques and theoretical approaches. This volume contains papers devoted to the theoretical representation and analysis of the 3D images. The related topics included are 3D image transformation, 3D tensor image representation, 3D content generation technologies, 3D graphic information processing, VR content generation technologies, multi-dimensional image processing, dynamic and auxiliary 3D displays, VR/AR/MR device, VR camera technologies, 3D imaging technologies and applications, 3D computer vision, 3D video communications, 3D medical images processing and analysis, 3D remote sensing images and systems, deep learning for image restoration and recognition, neural networks for MD image processing, etc.Table of ContentsColor Restoration of RGB-NIR Images in Low-light Environment Using CycleGAN.- A Novel Space Division Rough Set Model for Feature Selection.- Development of Mobile Food Recognition System Based on Deep Convolutional Network.- Image-Based Physics Rendering for 3D Surface Reconstruction: A Survey.- Network Intrusion Detection Based on Apriori-Kmeans Algorithm.- Global Analysis of Discrete S-I-R Models and S-I-S Systems.- Overview of SAR Image Change Detection Based on Segmentation.- Water Environmental Quality Assessment and Effect Prediction Based on Artificial Neural Network.- Full-Focus Imaging Detection of Ship Ultrasonic Phased Array Based on Directivity Function.- Longitudinal Structure Analysis and Segmentation Algorithm of Dongba Document.- Image Recognition Methods Based on Deep Learning.- Insulator Detection Study Based on Improved Faster-RCNN.- Comparative Analysis of Automatic Poetry Generation Systems Based on Different Recurrent Neural Networks.- Grid False Data Intrusion Detection Method Based on Edge Computing and Federated Learning.- Research on the Simulation of Informationized Psychological Sand Table Based on 3D Scene.- Innovative Design of Traditional Arts and Crafts Based on 3D Digital Technology.- Citrus Positioning Method Based On Camera And Lidar Data Fusion.- Research on Graphic Design of Digital Media Art based on Computer Aided Algorithm.- Ore Detection Method Based on YOLOv4.

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Book SynopsisThis book is a collection of the high-quality research articles in the field of computer vision and robotics which are presented in International Conference on Computer Vision and Robotics (ICCVR 2022), organized by BBD University Lucknow India, during 21 – 22 May 2022. The book discusses applications of computer vision and robotics in the fields like medical science, defence and smart city planning. This book presents recent works from researchers, academicians, industry, and policy makers.Table of ContentsStory Telling: Learning to Visualize Sentences Through Generated Scenes.- A Novel Processing of Scalable Web Log Data using Map Reduce Framework.- A Review of Disease Detection of Pre and Post-Harvest Plant Diseases: Recent Developments and Future.- Comparative Study Based on Lung Cancer with Covid-19 Using Deep Learning and Machine Learning.- Low-cost Data Acquisition System for Electric Vehicles.- Machine Learning based Robotic-Assisted Upper Limb Rehabilitation Therapies: A Review.- Performance Analysis of Classic LEACH vs CC-LEACH.- Anomaly Detection in the Course Evaluation Process.- Self Attention Based Efficient U-Net for Crack Segmentation.- Lung Carcinoma Detection from CT Images Using Image Segmentation.- A Deep Learning Based Human Activity Recognition System for Monitoring the Elderly People.- Tweets Classification on the Base of Sentiments using Deep Learning.

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Book SynopsisThis book presents selected research papers on current developments in the fields of soft computing and signal processing from the Fifth International Conference on Soft Computing and Signal Processing (ICSCSP 2022). The book covers topics such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning and discusses various aspects of these topics, e.g., technological considerations, product implementation and application issues.Table of ContentsChapter 1. Microservice Architecture Observability Tool Analysis.- Chapter 2. Decentralized payment architecture for e-commerce and utility transactions with Government verified identities.- Chapter 3. Detection of Phishing Website using Intelligent Machine Learning Classifiers.- Chapter 4. Bidirectional Gated Recurrent Unit (BiGRU) based Bitcoin Price Prediction by News Sentiment Analysis.- Chapter 5. How AI Algorithms are being used in Applications.- Chapter 6. A Framework for Identifying Theft Detection using Multiple-instance Learning.- Chapter 7. An Efficient Reversible Data Hiding Based on Prediction Error Expansion.- Chapter 8. Deriving Insights from COVID-19.- Chapter 9. Smoke Detection in Forest Using Deep Learning.- Chapter 10. Pneumothorax Segmentation using Feature Pyramid Network and MobileNet Encoder through Radiography Images.- Chapter 11. Visual Learning with Dynamic Recall.- Chapter 12. Machine learning for drug discovery using ag-glomerative hierarchical clustering.- Chapter 13. Automated Photomontage Generation with Neural Style Transfer.- Chapter 14. Machine Learning Model Development Using Computational Neurology.- Chapter 15. Graph Theory based user profile extraction and community detection in Linkedin- A study. etc.

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Book SynopsisThis book reviews the most powerful attack strategies and potential defense mechanisms, always approaching the interplay between the Fusion Center and the Byzantines from a game-theoretic perspective. For each of the settings considered, the equilibria of the game and the corresponding payoffs are derived, shedding new light on the achievable performance level and the impact that the presence of the Byzantines has on the accuracy of decisions made by the Fusion Center. Accordingly, the book offers a simple yet effective introduction to the emerging field of adversarial information fusion, providing a wealth of intuitive take-home lessons for practitioners interested in applying the most basic notions to the design of practical systems, while at the same time introducing researchers and other readers to the mathematical details behind the theory. Table of ContentsIntroduction.- Preliminaries.- Security attacks and defenses in distributed sensor networks.- A Heuristic defense: A soft isolation algorithm for adversarial decision fusion.- Optimum decision fusion in the presence of Byzantines.- Nearly optimum decision fusion via message passing.- Decision fusion of hidden-Markov observations with synchronized attacks.- Decision fusion with unbalanced priors.- Decision fusion game with incomplete knowledge in a Bayesian setup.- Conclusions.

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Book SynopsisThis book is devoted to the application of advanced signal processing on event-related potentials (ERPs) in the context of electroencephalography (EEG) for the cognitive neuroscience. ERPs are usually produced through averaging single-trials of preprocessed EEG, and then, the interpretation of underlying brain activities is based on the ordinarily averaged EEG. We find that randomly fluctuating activities and artifacts can still present in the averaged EEG data, and that constant brain activities over single trials can overlap with each other in time, frequency and spatial domains. Therefore, before interpretation, it will be beneficial to further separate the averaged EEG into individual brain activities. The book proposes systematic approaches pre-process wavelet transform (WT), independent component analysis (ICA), and nonnegative tensor factorization (NTF) to filter averaged EEG in time, frequency and space domains to sequentially and simultaneously obtain the pure ERP of interest. Software of the proposed approaches will be open-accessed.Table of ContentsIllustrations of Digital Filter, Fourier Transform and Wavelet Transform by the Definition of Correlation; Wavelet Filter Design Based on Frequency Responses for Filtering ERP Data with Duration of One Epoch; Individual-Level Independent Component Analysis to Extract ERPs' Components from Averaged EEG Data Over Single Trials; Multi-Domain Feature of an ERP Extracted by Nonnegative Tensor Factorization: New Approach for Group-Level Analysis of EEPs; Analysis of Ongoing EEG During Real-World Music Experiences by Nonnegative Tensor Factorization;

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Book SynopsisThe volume is a collection of best selected research papers presented at International Conference on Advances in Data-driven Computing and Intelligent Systems (ADCIS 2022) held at BITS Pilani, K K Birla Goa Campus, Goa, India during 23 – 25 September 2022. It includes state-of-the art research work in the cutting-edge technologies in the field of data science and intelligent systems. The book presents data-driven computing; it is a new field of computational analysis which uses provided data to directly produce predictive outcomes. The book will be useful for academicians, research scholars, and industry persons.Table of ContentsScenario Based Neural Network Model for Integrated Lighting Schemes in Residential Buildings.- Electrical Muscle Stimulation Models Identification Based on Hammerstein Structure and Gravitational Search Algorithm.- Experimental analysis of “A novel swarm intelligence optimization approach: sparrow search algorithm”.- Solving FJSP using Multi-agent system with GA.- A Comparative Analysis on Optimal Power Allocation and Pairing of User in Downlink NOMA System.

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Book SynopsisThis book provides an overview on the current progresses in artificial intelligence and neural nets in data science. The book is reporting on intelligent algorithms and applications modeling, prediction, and recognition tasks and many other application areas supporting complex multimodal systems to enhance and improve human–machine or human–human interactions. This field is broadly addressed by the scientific communities and has a strong commercial impact since investigates on the theoretical frameworks supporting the implementation of sophisticated computational intelligence tools. Such tools will support multidisciplinary aspects of data mining and data processing characterizing appropriate system reactions to human-machine interactional exchanges in interactive scenarios. The emotional issue has recently gained increasing attention for such complex systems due to its relevance in helping in the most common human tasks (like cognitive processes, perception, learning, communication, and even "rational" decision-making) and therefore improving the quality of life of the end users.Table of Contents1. Michele Scarpiniti, Edoardo Massaro, Danilo Comminiello and Aurelio Uncini: Generating New Sounds by Vector Arithmetic in the Latent Space of the MelGAN Architecture2. Kamyar Zeinalipour and Marco Gori: Graph Neural Networks for Topological Feature Extraction in ECG Classification3. Francesco Camastra, Angelo Casolaro and Gennaro Iannuzzo: Manifold Learning by a Deep Gaussian Process Variational Autoencoder4. Marcos Faundez-Zanuy, Anna Faura-Pujol, Hector Montalvo-Ruiz, Alexia Losada-Fors, Pablo Genovese and Pilar Sanz-Cartagena: Analysis of Sensors for Movement Analysis5. Giansalvo Cirrincione, Vincenzo Randazzo, Pietro Barbiero, Gabriele Ciravegna and Eros Pasero: Dual Seep Clustering6. Vincenzo Randazzo, Gaia Marchetti, Carla Giustetto, Erica Gugliermina, Rahul Kumar, Giansalvo Cirrincione, Fiorenzo Gaita and Eros Pasero: Learning-Based Approach to Predict Fatal Events in Brugada Syndrome7. Francesco Prinzi, Marco Insalaco, Salvatore Gaglio and Salvatore Vitabile: Breast Cancer Localization and Classification in Mammograms Using YoloV58. Jonathan Melchiorre, Marco Martino Rosso, Raffaele Cucuzza, Emanuela D'Alto, Amedeo Manuello Bertetto and Giuseppe Carlo Marano: Deep Acoustic Emission Detection Trained on Seismic Signals9. Elena Sibilano, Michael Lassi, Alberto Mazzoni, Vitoantonio Bevilacqua and Antonio Brunetti: A Deep Learning Framework for the Classification of Pre-Prodromal and Prodromal Alzheimer’s Disease Using Resting-State EEG signals10. Giovanni Di Gennaro, Amedeo Buonanno, Francesco Verolla, Giovanni Fioretti, Francesco A. N. Palmieri, and Krishna R. Pattipati: Imitation Learning Through Prior Injection in Markov Decision Processes 11. Giovanni Di Gennaro, Amedeo Buonanno, Marilena Baldi, Enzo Capoluongo, and Francesco A.N. Palmieri: Vision-Based Human Activity Recognition Methods Using Pose Estimation12. Stefano Fiscale, Laura Inno, Angelo Ciaramella, Alessio Ferone, Alessandra Rotundi, Pasquale De Luca, Ardelio Galletti, Livia Marcellino and Giovanni Covone: Identifying Exoplanets in TESS Data by Deep Learning13. Vincenzo Bevilacqua, Antonio Di Marino, Angelo Ciaramella, Anastasia Angela Biancardi, Giorgio Budillon, Paola de Ruggiero, Emanuele Della Volpe, Luigi Gifuni, Danilo Mascolo, Stefano Pierini and Enrico Zambianchi: Computational Intelligence for Marine Litter Recovery14. Alessio Ferone, Marco Lazzaro, Vincenzo Mariano Scarrica, Angelo Ciaramella and Antonino Staiano: A Synthetic Dataset for Learning Optical Flow in Underwater Environment15. Giorgia Ghione, Marta Lovino, Elisa Ficarra and Giansalvo Cirrincione: An Interpretable BERT-Based Architecture for SARS-CoV-2 Variant Identification16. Michele Fedrizzi and Silvio Giove: Competence-Based Coalition Choice, a Non-Additive Approach17. Michele La Rocca, Cira Perna, Marilena Sibillo and Antonio Vignes: Forecasting Mortality with Autoencoders: An Application to Italian Mortality Data.18. Michele Scarpiniti, Edoardo Bini, Marco Ferraro, Alessandro Giannetti, Danilo Comminiello, Yong-Cheol Lee and Aurelio Uncini: Leaky Echo State Network for Audio Classification in Construction Sites19. Sidhant Kumar, Vijayeskar Kumar, Krishnil Ram, Michael Wood, Giansalvo Cirrincione and Rahul Kumar: ECG Signal Classification Using Long-Short-Term-Memory Neural Networks20. Michele Lo Giudice, Nadia Mammone, Cosimo Ieracitano, Umberto Aguglia, Danilo Mandic and Francesco Carlo Morabito: A Convolutional Neural Network Approach for the Classification of Subjects with Epileptic Seizures vs Psychogenic Non-Epileptic Seizures and Control Based on Automatic Feature Extraction from Empirical Mode Decomposition of Interictal EEG Recordings21. Nicola Camatti, Andrea Ellero and Paola Ferretti: Commerce Districts: Conditions for Customer Overall Satisfaction in a Multi-Attribute Framework22. Andrea Ellero, Paola Ferretti, and Elena Zocchia: Problematic Merging and Cartels: A Collusion Risk Factors Analysis

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Book SynopsisThis book presents the select peer-reviewed proceedings of the 2nd International Conference on Emerging Electronics & Automation (E2A) 2022. The proceedings aim to provide the reader with a view of the latest scientific efforts and achievements of the participants in the emerging fields including instrumentation, control, signal processing, communication, and associated computational techniques. It covers diverse fields of electronics, computation, automation, microelectronic technology, nanomaterials, and biomedical engineering applications. This volume will be of interest to those in academia and industry.Table of ContentsA Computational Aspect to Analyse Impact of Nutritional Status on the Development of Cardiovascular Diseases.- Vernacular Language Handwriting Recognition using Deep Learning Techniques.- FPGA Implementation of Efficient Softmax Architecture for Deep Neural Networks.- Multi-stage and multi-objective dynamic optimization-based scheduling of uncertain hybrid renewable energy systems with real-time energy compensation.- Design of Regenerative Snubber Circuit for Motor Drivers.- Clustering based multi-objective stochastic optimization approach in scheduling optimal energy dispatch of multiple energy sources in the presence of uncertainty.- Unfalsified Adaptive Control of a Robotic System.- Semi-Active Control for Seismic Vibration Mitigation of Building System with Magnetorheological Damping Device.- Relative Ageing of Population and Subpopulations in Proportional Reversed Hazard Frailty Models.- Handwritten Word Recognition in English Language.- Digital Image Watermarking Using Integer Wavelet Transform and Singular Value Decomposition.- Effect of Shallow Learning Techniques and Feature Selection for Breast Cancer Detection.- Design and Development of a Optimized Fast Transformation Module (OpFTM) for GAN Accelerator with Computation Efficiency.- A Meta-heuristic Optimized-based Classification Intrusion Detection System for BoT-IoT.- Fusion Spectrogram for Sound Classification Using 2D Convolutional Neural Network.- Design and Implementation of Garbage Detection and Classification Using YOLO-V5.- Simulations towards design of Matching Layer in Acoustic Emission Sensor.- Virtual Impedance Based Advanced Droop Control for Improved Dynamic Power Sharing in Islanded Microgrid.- A Parallel Signal Detector Approach for Detection of Human Activities Using Multiple Seismic Sensors.- Study of Dielectric Characteristics of Forsterite Based Medical Implant.- Performance Evaluation and Assessment of 100kW Grid Tied SPV System in Subtropical Climatic Conditions.- Analysis and Experimental Validation of SPWM and SVPWM Techniques on Two-level Three-phase VSI.- Performance Analysis of Fuzzy Logic with P&O MPPT for Grid Connected Solar PV System under Varying Solar Irradiance.- Switched-Boost-Modified Z-Source Inverter for Renewable Energy Application.- Vibration Energy Harvester using piezoelectric with truncated cone rectangular beam structure for low power applications.

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